Quality requirements of manufactured products or parts are given in the form of specification limits on the quality characteristics of individual units. If a product is to meet the customer’s fitness for use criteria, it should be produced by a process which is stable or repeatable. In other words, it must be capable of operating with little variability around the target value or nominal value of the product’s quality characteristic. In order to maintain and improve product quality, we need to apply statistical process control techniques such as histogram, check sheet, Pareto chart, cause and effect diagram, or control charts. Among those techniques, the most important one is control charting. The cumulative sum (CUSUM) control charts have been used in statistical process control (SPC) in industries for monitoring process shifts and supporting online measurement. The objective of this research is to apply Taguchi's quality loss function concept to cost based CUSUM control chart design. In this study, a modified quality loss function was developed to reflect quality loss situation where general quadratic loss curve is not appropriate. This research also provided a methodology for the design of CUSUM charts using Taguchi quality loss function concept based on the minimum cost per hour criterion. The new model differs from previous models in that the model assumes that quality loss is incurred even in the incontrol period. This model was compared with other cost based CUSUM models by Wu and Goel, According to numerical sensitivity analysis, the proposed model results in longer average run length in in-control period compared to the other two models.

Today, conventional CVT equipped vehicle controls engine torque and gear ratio by using engine torque map and shifting map. But this control process is difficult to optimize the fuel economy when the driving mode is changed arbitrary. In this study, I propose the real-time CVT control with considering the power loss of transmission system to improve vehicle fuel economy and drivability. The driving performance and fuel economy of the proposed control logic is analyzed by backward simulation and the validity of new control logic is verified.

Control Chart is a graph which dots the characteristic values of a process. It is the tool of statistical technique to keep a process in controlled condition. It is also used for investigating the state of a process. Therefore many companies have used Control Chart as the tool of statistical process control (SPC). Products from a production process represent accidental dispersion values around a certain reference value. Fluctuations cause of quality dispersion is classified as a chance cause and a assignable cause. Chance cause refers unmanageable practical cause such as operator proficiency differences, differences in work environment, etc. Assignable cause refers manageable cause which is possible to take actions to remove such as operator inattention, error of production equipment, etc. Traditionally x-R control chart or x-s control chart is used to find and remove the error cause. Traditional control chart is to determine whether the measured data are in control or not, and lets us to take action. On the other hand, RNELCC (Reflected Normal Expected Loss Control Chart) is a control chart which, even in controlled state, indicates the information of economic loss if a product is in inconsistent state with process target value. However, contaminated process can cause control line sensitive and cause problems with the detection capabilities of chart. Many studies on robust estimation using trimmed parameters have been conducted. We suggest robust RNELCC which used the idea of trimmed parameters with RNEL control chart. And we demonstrate effectiveness of new control chart by comparing with ARL value among traditional control chart, RNELCC and robust RNELCC.

Control chart is representative tools of statistical process control (SPC). It is a graph that plotting the characteristic values from the process . It has two steps (or Phase). First step is a procedure for finding a process parameters. It is called PhaseⅠ. This step is to find the process parameters by using data obtained from in-controlled process. It is a step that the standard value was not determined. Another step is monitoring process by already known process parameters from PhaseⅠ. It is called Phase Ⅱ. These control chart is the process quality characteristic value for management, which is plotted dot whether the existence within the control limit or not. But, this is not given information about the economic loss that occurs when a product characteristic value does not match the target value. In order to meet the customer needs, company not only consider stability of the process variation but also produce the product that is meet the target value. Taguchi’s quadratic loss function is include information about economic loss that occurred by the mismatch the target value. However, Taguchi’s quadratic loss function is very simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. Also, it can be well explained by only on condition that the normal process. Spiring proposed an alternative loss function that called reflected normal loss function (RNLF). In this paper, we design a new control chart for overcome these disadvantage by using the Spiring’s RNLF. And we demonstrate effectiveness of new control chart by comparing its average run length (ARL) with x-R control chart and expected loss control chart (ELCC).

Control chart is a graph of plotting dot in the process characteristic values. It is a statistical technique that can be known whether or not the in-control state in this step. In many companies have use as a statistical process control(SPC) tool. Control chart is the management process quality characteristic value, which is plotted dot is whether the existence within the control limits. But, this is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In that sence, expected loss control chart(EL control chart) is very effective process control tool. Because it is a process control chart in consideration to economic loss. The EL control chart is using the quadratic loss function of Taguchi. However, Taguchi’s quadratic loss function is simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. In this paper, we design a new control chart using the reflected normal loss function(RNLF). And we demonstrate its effectiveness by using the control chart performance comparison of EL control chart.

The purpose of this study was to examine the effects of adolescents’ game usage on game addiction and the mediation effects of withdrawal symptoms and loss of control. The subjects of the study was 6,499 elementary, middle and high school students included in the panel data from the survey conducted by The National Youth Policy Institute. For data analysis, SPSS WIN 21 and AMOS 21 programs were used to test the structural equation model by examining the relationships among game usage, withdrawal symptoms, loss of control, and game addiction. The results are as followings. First, adolescents’ average daily game playing hours and average daily game playing hours on holidays caused withdrawal symptoms and loss of control, increasing the possibility of game addiction. However, the relationship between the number of years of playing games and game addiction was not mediated by withdrawal symptoms and loss of control. This implies that playing computer games from young age does not necessarily lead to game addiction unless the students show withdrawal symptoms or lose control.

Control chart is representative tool of Statistical Process Control (SPC). But, it is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In order to manage the process, we should consider not only stability of the variation also produce products with a high degree of matching the target value that is most ideal quality characteristics. There is a need for process control in consideration of economic loss. In this paper, we design a new control chart using the quadratic loss function of Taguchi. And we demonstrate effectiveness of new control chart by compare its ARL with   control chart.

Control chart is a graph of plotting dot about the process characteristic values. It is a statistical technique that can be known whether or not the in-control state in this step. In many companies have use as a statistical process control(SPC) tool. Control chart is the management process quality characteristic value, which is plotted dot is whether the existence within the control limits. This is not given information about the economic loss that occurs when a product is produced characteristic value does not match the target value of the process. In order to manage the process, we should consider not only stability of the variation also produce products with a high degree of matching the target value that is most ideal quality characteristics. There is a need for process control in consideration of economic loss. In this paper, we design a new control chart using the quadratic loss function of Taguchi. Use the control chart performance comparison of x-R, which is a traditional control chart, we demonstrate its effectiveness.

We investigated eight active natural antimicrobials for preservation of functional beverages that are usually degraded by yeasts rather than by bacteria due to a high sugar content and a low pH. Five strains of yeasts (S. cerevisiae, Z. bailii, P. membranaefaciens, C. albicans, and P. Anomala) were tested with eight natural antimicrobial agents (ε-polylysine, yucca extract, vitamin B1 derivative, scutellaria baicalensis extract, chitooligosaccharid, allyl isothiocyanate, sucrose-fatty acid ester, and oligosaccharide). The lowest minimal inhibitory concentrations (MIC) were 10 ppm for oligosaccharide and sucrose-fatty acid ester against S. cerevisiae and Z. bailii, 10 ppm for allyl isothiocynate against P. membranaefaciens and C. albican, and 10 ppm for allyl isothiocynate and oligosaccharide against P. anomala . No growth were observed for five kinds of yeasts in functional beverages containing sodium benzonate at concentration of 0.015% or higher. The resistance of S. cerevisiae, Z. bailii, and P. Anomala against natural antimicrobial agents was lower than those of P. membranaefaciens and C. albican. Allyl isothiocyanate, oligosaccharide, and sucrose- fatty acid ester showed the highest antimicrobial activities among the eight tested antimicrobials. These results can be applied to develop new natural antimicrobial agents to improve microbial quality of functional beverages.

For the vast majority of geostationary satellites currently in orbit, station keeping activities including orbit determination and maneuver planning and execution are ground-directed and dependent on the availability of ground-based satellite control personnel and facilities. However, a requirement linked to satellite autonomy and survivability in cases of interrupted ground support is often one of the stipulated provisions on the satellite platform design. It is especially important for a geostationary military-purposed satellite to remain within its designated orbital window, in order to provide reliable uninterrupted telecommunications services, in the absence of ground-based resources due to warfare or other disasters. In this paper we investigate factors affecting the robustness of a geostationary satellite’s orbit in terms of the maximum duration the satellite’s station keeping window can be maintained without ground intervention. By comparing simulations of orbit evolution, given different initial conditions and operations strategies, a variation of parameters study has been performed and we have analyzed which factors the duration is most sensitive to. This also provides valuable insights into which factors may be worth controlling by a military or civilian geostationary satellite operator. Our simulations show that the most beneficial factor for maximizing the time a satellite will remain in the station keeping window is the operational practice of pre-emptively loading East-West station keeping maneuvers for automatic execution on board the satellite should ground control capability be lost. The second most beneficial factor is using short station keeping maneuver cycle durations.